The American economy changed rapidly in the last half-century. The National Income and Product Accounts (NIPA) were designed before these changes started. They have stretched to accommodate new and growing service activities, but they are still organized for an industrial economy. It is hard to fit finance into the measurement of national product and of economic growth, and similar problems bedevil efforts to include other intangible investments as well. I describe how our current accounts deal with these problems, and I argue that existing NIPA data fail to describe the future path of growth in our new economy because they lack output data on financial, human and social capital investments. They fail to show that the United States is consuming its capital stock now and will suffer later, rather like killing the family cow to have a steak dinner.
{"title":"Finance in Economic Growth: Eating the Family Cow","authors":"P. Temin","doi":"10.2139/ssrn.3346750","DOIUrl":"https://doi.org/10.2139/ssrn.3346750","url":null,"abstract":"The American economy changed rapidly in the last half-century. The National Income and Product Accounts (NIPA) were designed before these changes started. They have stretched to accommodate new and growing service activities, but they are still organized for an industrial economy. It is hard to fit finance into the measurement of national product and of economic growth, and similar problems bedevil efforts to include other intangible investments as well. I describe how our current accounts deal with these problems, and I argue that existing NIPA data fail to describe the future path of growth in our new economy because they lack output data on financial, human and social capital investments. They fail to show that the United States is consuming its capital stock now and will suffer later, rather like killing the family cow to have a steak dinner.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114868066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper examines the disruption of statistics with the publication of the 2015 Ireland GDP at +26.3 per cent year on year. The figure was greeted by international disbelief. Ireland’s statistical authorities reacted with the publication, for the main aggregates, of modified data in parallel with the official one, much less affected by the bias on value added. The bias resulted from the relocation in Ireland of a huge amount of intellectual property capital, of the dimension of the GDP itself.To fix the link between statistical representation and economic fact means to depart from the legal form to let the substance prevail, i.e. depart from the description given by business reports and administrative data.
{"title":"The Irish GDP in 2016. After the Disaster Comes a Dilemma","authors":"R. Tedeschi","doi":"10.2139/ssrn.3429861","DOIUrl":"https://doi.org/10.2139/ssrn.3429861","url":null,"abstract":"The paper examines the disruption of statistics with the publication of the 2015 Ireland GDP at +26.3 per cent year on year. The figure was greeted by international disbelief. Ireland’s statistical authorities reacted with the publication, for the main aggregates, of modified data in parallel with the official one, much less affected by the bias on value added. The bias resulted from the relocation in Ireland of a huge amount of intellectual property capital, of the dimension of the GDP itself.To fix the link between statistical representation and economic fact means to depart from the legal form to let the substance prevail, i.e. depart from the description given by business reports and administrative data.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122871531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: The study was conducted with the aim of assessing the impact of foreign trade on economic growth in Malawi from 1961 to 2016. The study has used a neoclassic economic growth model with gross domestic product, exports, imports, capital and labor force as variables of analysis. Using annual time series data on the variables for the period 1961 to 2016 from the World Bank Data Bank, Ordinary Least Squares regression and statistical accuracy of the findings was done at 5 percent level of significance. The four variables which included exports, imports, gross capital formation and labor force were found to have a positive effect on the country’s economic growth. Nevertheless, the study found an existing relationship between the variables. The above results strongly suggest that Malawi should continue with its foreign trade. The study recommends export diversification, investment in technology, increase capital good through imports and labor intensive industrialization.
{"title":"The Impact of Foreign Trade on Malawi Economic Growth","authors":"Nancy Chibaya","doi":"10.2139/ssrn.3510501","DOIUrl":"https://doi.org/10.2139/ssrn.3510501","url":null,"abstract":"Abstract: The study was conducted with the aim of assessing the impact of foreign trade on economic growth in Malawi from 1961 to 2016. The study has used a neoclassic economic growth model with gross domestic product, exports, imports, capital and labor force as variables of analysis. Using annual time series data on the variables for the period 1961 to 2016 from the World Bank Data Bank, Ordinary Least Squares regression and statistical accuracy of the findings was done at 5 percent level of significance. The four variables which included exports, imports, gross capital formation and labor force were found to have a positive effect on the country’s economic growth. Nevertheless, the study found an existing relationship between the variables. The above results strongly suggest that Malawi should continue with its foreign trade. The study recommends export diversification, investment in technology, increase capital good through imports and labor intensive industrialization.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129018584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on updated datasets of value added and of labour and capital inputs, this paper provides a reassessment of the proximate causes of Italy’s economic development since its political unification in 1861 to 2016. Italy’s pre-WWII economy featured weak productivity growth, with the exception of the Giolitti era and the 1920s. Italy then embarked on an exceptional catching-up process relative to the technological leaders during the Golden Age. Compared with the pre-WWII years, when the Italian economy was held back by slow productivity growth in the large agricultural sector, the catching-up process during the Golden Age was propelled by the rapid shift of labour out of agriculture. As in many countries, this rapid growth in productivity could not be sustained after 1973, but the further slowdown since the 1990s has been more pronounced in Italy than elsewhere. The disappointing performance of the Italian economy since the early 1990s is largely explained by slow labour productivity growth in the now dominant services sector and by sluggish aggregate total factor productivity. Labour productivity developments actually turned negative during the protracted crisis following the global financial turmoil, due to the decline in capital accumulation and in total factor productivity. Since the start of the recovery in 2013, while total factor productivity has returned to a moderately positive trend, the capital stock has not fully overcome the legacy of the crisis.
{"title":"Long-Run Trends in Italian Productivity","authors":"Claire Giordano, G. Toniolo, Francesco Zollino","doi":"10.2139/ssrn.3082193","DOIUrl":"https://doi.org/10.2139/ssrn.3082193","url":null,"abstract":"Based on updated datasets of value added and of labour and capital inputs, this paper provides a reassessment of the proximate causes of Italy’s economic development since its political unification in 1861 to 2016. Italy’s pre-WWII economy featured weak productivity growth, with the exception of the Giolitti era and the 1920s. Italy then embarked on an exceptional catching-up process relative to the technological leaders during the Golden Age. Compared with the pre-WWII years, when the Italian economy was held back by slow productivity growth in the large agricultural sector, the catching-up process during the Golden Age was propelled by the rapid shift of labour out of agriculture. As in many countries, this rapid growth in productivity could not be sustained after 1973, but the further slowdown since the 1990s has been more pronounced in Italy than elsewhere. The disappointing performance of the Italian economy since the early 1990s is largely explained by slow labour productivity growth in the now dominant services sector and by sluggish aggregate total factor productivity. Labour productivity developments actually turned negative during the protracted crisis following the global financial turmoil, due to the decline in capital accumulation and in total factor productivity. Since the start of the recovery in 2013, while total factor productivity has returned to a moderately positive trend, the capital stock has not fully overcome the legacy of the crisis.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126370874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Mccarthy, J. Sefton, Ronald D. Lee, Jože Sambt
We develop Generational Wealth Accounts (GWA): the first set of balance sheets, broken down by generations, to include all human capital, tangible wealth, financial wealth, and transfer wealth, and the uses to which these resources are put. We then use them to measure the size, nature (public or private; capital or current) and direction of inter-generational transfers and assess the sustainability of public and private consumption plans. We confirm that public sector consumption in the UK is unsustainable but show that the private sector is close to balance. Aggregate consumption plans are therefore unsustainable. Although public sector finances worsened significantly over the crisis, the private sector balance improved and capital transfers to the young increased, more than fully offsetting this deterioration. We find that increases in house prices redistributed resources away from the young and towards the old but had little effect on overall sustainability.
{"title":"Generational Wealth Accounts: Did Public and Private Inter-Generational Transfers Offset Each Other Over the Financial Crisis?","authors":"David Mccarthy, J. Sefton, Ronald D. Lee, Jože Sambt","doi":"10.2139/ssrn.3052381","DOIUrl":"https://doi.org/10.2139/ssrn.3052381","url":null,"abstract":"\u0000 We develop Generational Wealth Accounts (GWA): the first set of balance sheets, broken down by generations, to include all human capital, tangible wealth, financial wealth, and transfer wealth, and the uses to which these resources are put. We then use them to measure the size, nature (public or private; capital or current) and direction of inter-generational transfers and assess the sustainability of public and private consumption plans. We confirm that public sector consumption in the UK is unsustainable but show that the private sector is close to balance. Aggregate consumption plans are therefore unsustainable. Although public sector finances worsened significantly over the crisis, the private sector balance improved and capital transfers to the young increased, more than fully offsetting this deterioration. We find that increases in house prices redistributed resources away from the young and towards the old but had little effect on overall sustainability.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120981807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We demonstrate how Bayesian shrinkage can address problems with utilizing large information sets to calculate trend and cycle via a multivariate Beveridge-Nelson (BN) decomposition. We illustrate our approach by estimating the U.S. output gap with large Bayesian vector autoregressions that include up to 138 variables. Because the BN trend and cycle are linear functions of historical forecast errors, we are also able to account for the estimated output gap in terms of different sources of information, as well as particular underlying structural shocks given identification restrictions. Our empirical analysis suggests that, in addition to output growth, the unemployment rate, CPI inflation, and, to a lesser extent, housing starts, consumption, stock prices, real M1, and the federal funds rate are important conditioning variables for estimating the U.S. output gap, with estimates largely robust to incorporating additional variables. Using standard identification restrictions, we find that the role of monetary policy shocks in driving the output gap is small, while oil price shocks explain about 10% of the variance over different horizons.
{"title":"Estimating and Accounting for the Output Gap with Large Bayesian Vector Autoregressions","authors":"J. Morley, Benjamin Wong","doi":"10.2139/ssrn.3005741","DOIUrl":"https://doi.org/10.2139/ssrn.3005741","url":null,"abstract":"We demonstrate how Bayesian shrinkage can address problems with utilizing large information sets to calculate trend and cycle via a multivariate Beveridge-Nelson (BN) decomposition. We illustrate our approach by estimating the U.S. output gap with large Bayesian vector autoregressions that include up to 138 variables. Because the BN trend and cycle are linear functions of historical forecast errors, we are also able to account for the estimated output gap in terms of different sources of information, as well as particular underlying structural shocks given identification restrictions. Our empirical analysis suggests that, in addition to output growth, the unemployment rate, CPI inflation, and, to a lesser extent, housing starts, consumption, stock prices, real M1, and the federal funds rate are important conditioning variables for estimating the U.S. output gap, with estimates largely robust to incorporating additional variables. Using standard identification restrictions, we find that the role of monetary policy shocks in driving the output gap is small, while oil price shocks explain about 10% of the variance over different horizons.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115425503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Part of the debate about the ‘productivity puzzle’ concerns the potential mismeasurement of digital activities. Specific measurement adjustments explored in previous research appear not to make a quantitatively large difference to real GDP or productivity growth estimates. However, although these potential adjustments may be small individually, taken together they could be wide in scope and quantitatively significant. This paper sets out a taxonomy of the range of potential measurement artefacts arising from digital innovations. It also specifically considers digitally-enabled substitutions in activity across the production boundary. I argue that these, along with other substitutions occurring within the production boundary, go beyond the effects of digital considered in earlier research; and may be making a meaningful contribution to the productivity puzzle as measured on existing statistical definitions.
{"title":"Do-it-Yourself Digital: The Production Boundary and the Productivity Puzzle","authors":"D. Coyle","doi":"10.2139/ssrn.2986725","DOIUrl":"https://doi.org/10.2139/ssrn.2986725","url":null,"abstract":"Part of the debate about the ‘productivity puzzle’ concerns the potential mismeasurement of digital activities. Specific measurement adjustments explored in previous research appear not to make a quantitatively large difference to real GDP or productivity growth estimates. However, although these potential adjustments may be small individually, taken together they could be wide in scope and quantitatively significant. This paper sets out a taxonomy of the range of potential measurement artefacts arising from digital innovations. It also specifically considers digitally-enabled substitutions in activity across the production boundary. I argue that these, along with other substitutions occurring within the production boundary, go beyond the effects of digital considered in earlier research; and may be making a meaningful contribution to the productivity puzzle as measured on existing statistical definitions.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128666268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose and find that aggregate special items conveys more information about future real GDP growth than aggregate earnings before special items because the former contains advance news about future economic outcomes. A two-stage rational expectations test reveals that professional forecasters fully understand the information content of aggregate earnings before special items but underestimate that of aggregate special items when revising their GDP forecasts. Using vector autoregressions, we show that aggregate earnings before special items has predictive ability for GDP because, as suggested by previous literature, it acts as a proxy for corporate profits included in national income. In contrast, aggregate special items captures changes in the behavior of economic agents on a timely basis, which in turn have real effects on firms' investment and hiring, as well as consumers' wealth and spending. Consistent with news-driven business cycles, we find that aggregate special items produces synchronized movements across macroeconomic aggregates.
{"title":"From Accounting to Economics: The Role of Aggregate Special Items in Gauging the State of the Economy","authors":"Ahmed M. Abdalla, Jose M. Carabias","doi":"10.2139/ssrn.2871600","DOIUrl":"https://doi.org/10.2139/ssrn.2871600","url":null,"abstract":"We propose and find that aggregate special items conveys more information about future real GDP growth than aggregate earnings before special items because the former contains advance news about future economic outcomes. A two-stage rational expectations test reveals that professional forecasters fully understand the information content of aggregate earnings before special items but underestimate that of aggregate special items when revising their GDP forecasts. Using vector autoregressions, we show that aggregate earnings before special items has predictive ability for GDP because, as suggested by previous literature, it acts as a proxy for corporate profits included in national income. In contrast, aggregate special items captures changes in the behavior of economic agents on a timely basis, which in turn have real effects on firms' investment and hiring, as well as consumers' wealth and spending. Consistent with news-driven business cycles, we find that aggregate special items produces synchronized movements across macroeconomic aggregates.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114857740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Alexander, C. Dziobek, Marco A. Marini, E. Metreau, Michael Stanger
To derive real GDP, the System of National Accounts 2008 (2008 SNA) recommends a technique called double deflation. Some countries use single deflation techniques, which fail to capture important relative price changes and introduce estimation errors in official GDP growth. We simulate the effects of single deflation to the GDP data of eight countries that use double deflation. We find that errors due to single deflation can be significant, but their magnitude and direction are not systematic over time and across countries. We conclude that countries still using single deflation should move to double deflation.
{"title":"Measure Up: A Better Way to Calculate GDP","authors":"T. Alexander, C. Dziobek, Marco A. Marini, E. Metreau, Michael Stanger","doi":"10.2139/ssrn.3021995","DOIUrl":"https://doi.org/10.2139/ssrn.3021995","url":null,"abstract":"To derive real GDP, the System of National Accounts 2008 (2008 SNA) recommends a technique called double deflation. Some countries use single deflation techniques, which fail to capture important relative price changes and introduce estimation errors in official GDP growth. We simulate the effects of single deflation to the GDP data of eight countries that use double deflation. We find that errors due to single deflation can be significant, but their magnitude and direction are not systematic over time and across countries. We conclude that countries still using single deflation should move to double deflation.","PeriodicalId":135206,"journal":{"name":"ERN: Measurement & Data on National Income & Product Accounts (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134513185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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